Robust Query Processing for Personalized Information Access on the Semantic Web

Research in Cooperative Query answering is triggered by the observation that users are often not able to correctly formulate queries to databases that return the intended result. Due to a lack of knowledge of the contents and the structure of a database, users will often only be able to provide very broad queries. Existing methods for automatically refining such queries based on user profiles often overshoot the target resulting in queries that do not return any answer. In this paper, we investigate methods for automatically relaxing such over-constraint queries based on domain knowledge and user preferences. We describe a framework for information access that combines query refinement and relaxation in order to provide robust, personalized access to heterogeneous RDF data as well as an implementation in terms of rewriting rules and explain its application in the context of e-learning systems